An Efficient Model Predictive Current Control Algorithm for Grid-Connected Multi-Level Inverter with Computational Delay Compensation

摘要

This paper proposes an efficient model predictive current control (MPC) algorithms for grid-connected multi-level (ML) inverter. The proposed algorithm utilizes the discrete-time model to predict the future behavior of the grid connected inverter (GCI) to fulfil the control objectives: fast dynamic and low ripples of the grid current, balancing of the capacitor voltages and minimizing the switching number. These threes control objectives are incorporated in single cost function calculated and evaluated for each switching state $S_{abc}^{opt}$ available in the inverter, to generate the optimal switching state applied directly to the inverter. Moreover, a considerable computational delay is required to generate $S_{abc}^{opt}$. Furthermore, the contributions of the paper is not only the compensation of the computational delay using a long horizon prediction approach, but also using the three-level neutral point clamped (3L-NPC) inverter to provide a low ripples grid current and decrease the control complexity. Finally, the efficiency of the proposed compensation demonstrated through simulations results.